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Weekly links Jan 12: Big Thinkers brought down to size, can you beat the World Bank at predicting poverty? Chinese minimum wage rises all get spent, three job openings, and more…

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  • Duncan Green summarizes Stefan Dercon’s view of 10 top thinkers in development. E.g. on Acemoglu and Robinson “their policy advice is just ‘buy yourself a better history/don’t start from here’. Not very useful for aid”. Alice Evans responds to the lack of women on Stefan’s list with five big problems in development and female scholars to learn from on these.
  • How did Chinese consumption respond to changes in the minimum wage? Dautovic and co-authors on VoxEU report that “For the period 2002-2009, we identify more than 13,874 changes in the local minimum wage across China's 2,183 counties and 285 cities…many counties experienced substantial nominal increases in their minimum wage above 20%...we show that low-income households spend their entire additional income from a higher minimum wage…for poorer households, 40% of the additional minimum wage income is spend on health care and educational expenditure”
  • Looking to try out machine learning for poverty prediction? The World Bank has launched a competition (with prize money) to see how well you can predict poverty.

Six Questions with Mark Rosenzweig

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Mark Rosenzweig is Frank Altschul Professor of International Economics at Yale University, and was one of the original leaders in bringing theory and micro-level data to addressing development questions. We caught up with him after a recent symposium, which honored his achievements, and celebrated him turning 70 and continuing to produce important new work.

Statistical Power and the Funnel of Attribution

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Often there are many steps or stages between the starting point of some intervention and its ultimate goal, and at each step, people can drop out. The result can be extremely low power to measure impacts on this end outcome, even though we might be able to detect impacts on the intermediate steps. This post illustrates this point, with the goal of making clear the importance of trying to measure intermediate outcomes, and concludes with suggestions of ways to partially overcome this problem.

Top Ten Development Impact Blog Posts of 2017

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Weekly links Jan 5: papers you should have read last year, how to measure early childhood development 147 ways, move people to where the jobs are, and more…

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12 of our favorite development papers of the year

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Development Impact will now be on break over the next couple of weeks for the holidays, resuming in early January after the AEA annual meetings. Inspired by some of the interesting lists of favorite papers of the year (e.g. Noah Smith, Matt Notowidigdo) we thought we’d each offer three of our favorite development economics papers for the year...

How do household contributions to public goods respond to cash transfers? Guest post by Michael Walker

This is the eighteenth and final entry in this year's job market series. You can read them all here

A central question in development economics is how to fund public goods. Informal taxation, whereby households make direct contributions to local public goods (such as water resources, roads and schools) outside of the formal tax system, is an important source of funding for public goods in many low-income countries, especially Kenya (Olken and Singhal 2011, Ngau 1987, Barkan and Holmquist 1986). Informal taxes are coordinated and collected by local leaders and enforced via social sanctions rather than the state. In a formal tax system, legal statutes dictate how taxes change with household income. But how does informal taxation respond to changes in household income?  

My job market paper first quantifies informal taxation in Kenya. Using household panel data, I estimate informal tax schedules over the income distribution and test whether informal taxes respond to changes in earned income. Second, I estimate how informal taxation and public goods respond to a large, one-time increase in income from a randomized unconditional cash transfer program targeting poor households.   

The Earlier the Better? Timing and Type of Investments to Mitigate Early-Life Shocks: Guest post by Valentina Duque

This is the seventeenth, and penultimate, of this year’s job market series.
Research question and motivation
 That early-life events can affect adult outcomes is now well established. Lifelong health, education, and wages are all shaped by events of the in-utero and early-childhood environments (Barker 1992Cunha and Heckman, 2007Almond et al., 2017). To the extent that adverse shocks can often not be prevented, a key task for researchers and policymakers is to ascertain the potential for and degree of mitigation: Could investing in children's health and education help reduce gaps caused by early-life adversities?
In my job-market paper, we study whether the returns on human capital investments on children differ by exposure to adverse early-life shocks. We focus on two shocks that significantly affect households in developing countries: adverse weather shocks -- i.e., floods and droughts, which reduce children's initial skills--, and the introduction of conditional cash transfers (CCTs), which provide monetary subsidies to families with young children conditional on investments in children's health and education. In particular, we provide empirical evidence on how the effects of CCTs on children's long-term educational outcomes interact with children's early-life exposure to adverse weather shocks.

Weekly links December 15: non-frivolous frivolous expenses, Indian internal borders, aspirations, and much more…

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Why don’t people migrate more? A lab experiment of sequential decision-making: Guest post by Zach Barnett-Howell

This is the sixteenth in this year’s job market series

Darling you got to let me know // Should I stay or should I go?
One way to escape poverty is to leave it behind. Literally. Moving from a poorer to richer area is so advantageous for individuals that an entire literature on migration has developed to explain why more people don't move.

If you say that you are mine // I’ll be here ‘till the end of time
Bryan, Chowdhury, and Mobarak conducted an experiment in northwestern Bangladesh to induce migration. They offered households a small subsidy to migrate, a round-trip bus ticket worth $8.50. This proved sufficient for people to migrate, and those who migrated earned more and enjoyed higher levels of welfare. So it brought up a new question: why hadn’t those households already decided to migrate?
This immobility is problematic because it’s not supposed to happen. Foundational migration theories, like the Harris-Todaro model, were designed to explain movement from poorer to richer areas. These migrations made sense: people were arbitraging wages and other amenities across space, receiving more by being elsewhere. But how can we explain the opposite—people who don’t migrate—when the welfare gains would be tremendous?

If I go, there will be trouble // if I stay it will be double
In my job market paper I explain why people rationally would not make moves that offer higher welfare. I do this by modeling migration as a sequential decision where people try to figure out which location would suit them best.